Instructions to use Manas2708/bert-base-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Manas2708/bert-base-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Manas2708/bert-base-sentiment-analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Manas2708/bert-base-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("Manas2708/bert-base-sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Card for Model ID
This is a Text Classification Model, which is trained for Sentiment Analysis of Twitter Tweets
Model Details
Model Description
This is the model card of a ๐ค transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by: Manas Kulkarni
- Language(s) (NLP): English
- Finetuned from model [optional]: google-bert\bert-base-uncased
Uses
- Text Classification
- Downloads last month
- 26
Model tree for Manas2708/bert-base-sentiment-analysis
Base model
google-bert/bert-base-uncased